Stereo-electroencephalography-guided radiofrequency thermocoagulation in patients with MRI-negative focal epilepsy.

OBJECTIVE: Coupled with stereo-electroencephalography (SEEG), radiofrequency thermocoagulation (RFTC) has emerged as a therapeutic alternative for patients with refractory focal epilepsy, with proven safe but highly variable results across studies. The authors aimed to describe the outcomes and safety of SEEG-RFTC, focusing on patients with MRI-negative epilepsy. METHODS: A retrospective observational study was conducted on patients evaluated by SEEG in the authors' center. Of 84 total cases, 55 underwent RFTC, with 31 MRI-negative epilepsies that were ultimately included in the study. The primary outcome was freedom from disabling seizures at last follow-up. Secondary outcomes were reduction in seizure frequency (RFTC response = seizure frequency reduction > 50%), peri-interventional complications, and neuropsychological outcomes. Potential factors influencing post-RFTC outcome were considered by comparing different variables between responders and nonresponders. RESULTS: The mean follow-up period was 30.9 months (range 7.1-69.8 months). Three patients underwent subsequent resection/laser interstitial thermal therapy within the 1st year after RFTC failure. All other patients completed a minimum follow-up period of 1 year. Fourteen patients (45.2%) showed at least a 50% reduction in seizure frequency (responders), and 8 were seizure free (25.8% of the whole cohort). One case showed a permanent complication not directly related to thermolesions. Most patients (76%) showed no significant cognitive decline. Electrically elicited seizures (EESs) were observed in all seizure-free patients and were more frequent in responders (p = 0.038). All patients who were seizure free at the 6-month visit maintained their status during long-term follow-up. CONCLUSIONS: SEEG-RFTC is a safe procedure and leads to a good response in many cases of MRI-negative focal epilepsies. One-quarter of the patients were seizure free and almost one-half were responders at the last follow-up. Although these results are still far from those achieved through conventional resection, a nonnegligible proportion of patients may benefit from this one-stage and much less invasive approach. Factors associated with seizure outcome remain to be elucidated; however, responders were significantly more frequent among patients with EESs, and achieving 6 months of seizure freedom appears to predict a good long-term response. In addition, the positive predictive value of RFTC response may be a valuable factor in the decision to proceed to subsequent surgery.

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

Atlas of lesion locations and postsurgical seizure freedom in focal cortical dysplasia: A MELD study.

OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

Mood Disturbances, Anxiety, and Impact on Quality of Life in Patients Admitted to Epilepsy Monitoring Units.

Introduction: The overall combined prevalence of anxiety and depression in patients with epilepsy has been estimated at 20.2 and 22.9%, respectively, and is considered more severe in drug-refractory epilepsy. Patients admitted to epilepsy monitoring units constitute a particular group. Also, patients with psychogenic non-epileptic seizures can reach more than 20% of all admissions. This study aims to characterize these symptoms in a large cohort of patients admitted for evaluation in a tertiary epilepsy center. Materials and Methods: The study was conducted among 493 consecutive patients (age: 38.78 ± 12.7, 57% females) admitted for long-term video EEG from January 2013 to February 2021. Demographic, clinical, and mood disorder patients' data were collected. Anxiety and depression symptoms were assessed through the Hospital Anxiety Depression Scale (HADS-A and HADS-D), the State Trait Anxiety Inventory (STAI), and Beck Depression Inventory (BDI-II). Quality of life was determined using the QOLIE-10. Patients were divided into three groups: patients with epilepsy (n = 395), psychogenic non-epileptic seizures (PNES) (n = 56), and combined (n = 33). A univariate and multivariate regression analysis was performed for variables associated with quality of life. Results: Of 493 patients, 45.0% had structural etiology, and considering epilepsy classification, 43.6% were of temporal lobe origin. In addition, 32.45% of patients had a previous psychiatric history, 49.9% of patients had depressive symptoms in BDI, and 30.9% according to HADS-D; 56.42 and 52.63% of patients presented pathological anxiety scores in STAI-T and STAI-S, respectively; and 44.78% according to HADS-A. PNES and combined groups revealed a higher incidence of pathologic BDI scores (64.29 and 78.79%, p < 0.001) as well as pathologic HADS-A scores (p = 0.001). Anxiety and depression pathologic results are more prevalent in females, HADS-A (females = 50.7%, males = 36.8%; p = 0.0027) and BDI > 13 (females = 56.6%, males = 41.0%; p = 0.0006). QOLIE-10 showed that 71% of the patients had their quality of life affected with significantly higher scores in the combined group than in the epilepsy and PNES groups (p = 0.0015). Conclusions: Subjective anxiety, depression, and reduced quality of life are highly prevalent in patients with refractory epilepsy. These symptoms are more evident when PNES are associated with epilepsy and more severe among female patients. Most of the cases were not previously diagnosed. These factors should be considered in everyday clinical practice, and specific approaches might be adapted depending on the patient's profile.

Voxel-based morphometry for the evaluation of patients with pharmacoresistant epilepsy with apparently normal MRI.

BACKGROUND AND PURPOSE: Magnetic resonance imaging (MRI) is essential in the diagnosis of pharmacoresistant epilepsy (PRE), because patients with lesions detected by MRI have a better prognosis after surgery. Focal cortical dysplasia (FCD) is one of the most frequent etiologies of PRE but can be difficult to identify by MRI. Voxel-based morphometric analysis programs, like the Morphometric Analysis Program (MAP), have been developed to help improve MRI detection. Our objective was to evaluate the clinical usefulness of MAP in patients with PRE and an apparently normal MRI. METHODS: We studied 70 patients with focal PRE and a nonlesional MRI. The 3DT1 sequence was processed with MAP, obtaining three z-score maps. Patients were classified as MAP+ if one or more z-score maps showed a suspicious area of brightness, and MAP- if the z-score maps did not show any suspicious areas. For MAP+ cases, a second-look MRI was performed with a dedicated inspection based on the MAP findings. The MAP results were correlated with the epileptogenic zone. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: Thirty-one percent of patients were classified as MAP+ and 69% were MAP-. Results showed a sensitivity of 0.57, specificity of 0.8, PPV of 0.91, and NPV of 0.35. In 19% of patients, an FCD was found in the second-look MRI after MAP. CONCLUSIONS: MAP was helpful in the detection of lesions in PRE patients with a nonlesional MRI, which could have important repercussions for the clinical management and postoperative prognosis of these patients.

SYLVIUS: A multimodal and multidisciplinary platform for epilepsy surgery.

BACKGROUND AND OBJECTIVE: We present SYLVIUS, a software platform intended to facilitate and improve the complex workflow required to diagnose and surgically treat drug-resistant epilepsies. In complex epilepsies, additional invasive information from exploration with stereoencephalography (SEEG) with deep electrodes may be needed, for which the input from different diagnostic methods and clinicians from several specialties is required to ensure diagnostic efficacy and surgical safety. We aim to provide a software platform with optimal data flow among the different stages of epilepsy surgery to provide smooth and integrated decision making. METHODS: The SYLVIUS platform provides a clinical workflow designed to ensure seamless and safe patient data sharing across specialities. It integrates tools for stereo visualization, data registration, transfer of electrode plans referred to distinct datasets, automated postoperative contact segmentation, and novel DWI tractography analysis. Nineteen cases were retrospectively evaluated to track modifications from an initial plan to obtain a final surgical plan, using SYLVIUS. RESULTS: The software was used to modify trajectories in all 19 consulted cases, which were then imported into the robotic system for the surgical intervention. When available, SYLVIUS provided extra multimodal information, which resulted in a greater number of trajectory modifications. CONCLUSIONS: The architecture presented in this paper streamlines epilepsy surgery allowing clinicians to have a digital clinical tool that allows recording of the different stages of the procedure, in a common multimodal 2D/3D setting for participation of different clinicians in defining and validating surgical plans for SEEG cases.

Low entropy map of brain oscillatory activity identifies spatially localized events: A new method for automated epilepsy focus prediction.

The spatial mapping of localized events in brain activity critically depends on the correct identification of the pattern signatures associated with those events. For instance, in the context of epilepsy research, a number of different electrophysiological patterns have been associated with epileptogenic activity. Motivated by the need to define automated seizure focus detectors, we propose a novel data-driven algorithm for the spatial identification of localized events that is based on the following rationale: the distribution of emerging oscillations during confined events across all recording sites is highly non-uniform and can be mapped using a spatial entropy function. By applying this principle to EEG recording obtained from 67 distinct seizure epochs, our method successfully identified the seizure focus on a group of ten drug-resistant temporal lobe epilepsy patients (average sensitivity: 0.94, average specificity: 0.90) together with its characteristic electrophysiological pattern signature. Cross-validation of the method outputs with postresective information revealed the consistency of our findings in long follow-up seizure-free patients. Overall, our methodology provides a reliable computational procedure that might be used as in both experimental and clinical domains to identify the neural populations undergoing an emerging functional or pathological transition.

Underdiagnosis of Unilateral Spatial Neglect in stroke unit.

OBJECTIVES: Unilateral spatial neglect (USN) is the incapacity to respond to stimuli presented opposite to a dysfunctional cerebral hemisphere. It is usually caused by non-dominant hemisphere lesions, leads to poorer prognosis and might be underdiagnosed. The objectives of the study were to ascertain the presence of USN in acute stroke patients and analyze the possible degree of underdiagnosis in a Stroke Unit. MATERIALS AND METHODS: Prospective study of consecutive non-dominant hemisphere stroke patients within a period of 21 months. "Line Bisection" and "Triangles Cancellation" tests were used for USN screening and "Circle Gap Detection Task" to confirm the USN. The results were compared with routine Stroke Unit assessment using the NIHSS to determine the possible degree of underdiagnosis. RESULTS: A total of 62 subjects, 38 women (61.29%), mean age of 74.05 (SD 10.5) years, were included. USN was diagnosed in 25 cases (40.3%) but 56% of them were not detected in routine evaluation using the NIHSS. CONCLUSIONS: Unilateral spatial neglect, a common cognitive deficit after acute stroke, is greatly underdiagnosed in routine Stroke Unit assessment. The use of simple USN-specific screening tools would improve diagnosis and therefore the possibility of implementing appropriate rehabilitation strategies.